[yaml] add RunInference support with VertexAI #33406
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Signed-off-by: Jeffrey Kinard <[email protected]>
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R: @robertwb |
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R: @damccorm |
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| def underlying_handler(self): | ||
| return self._handler | ||
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| def preprocess_fn(self, row): |
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This won't actually get called until runtime, right? Perhaps we should call this default_preprocess_fn() and have it return an lambda (or raise an error). And then change postprocess_fn for symmetry.
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Great suggestion, I ended up making the preprocess parameter required on the VertexAI handler, so the error is redundant in this case... but I think moving forward it could be useful, and the refactor in general is cleaner.
Signed-off-by: Jeffrey Kinard <[email protected]>
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| def inference_output_type(self): | ||
| return RowTypeConstraint.from_fields([('example', Any), ('inference', Any), |
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Could we ask the handler for the type of inference? (Presumably the example type is that of the input as well.) Some handlers may not be able to provide this, but some can.
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We don't generally today, but we could for a very limited set of handlers. The ones I can think of with predictable output types are hugging face pipelines and vLLM; the rest are all dependent on the model.
I think this is probably worth doing when we can, it probably requires some slight modification to the PredictionResult type, though, and might be worth scoping into a follow on PR.
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| def inference_output_type(self): | ||
| return RowTypeConstraint.from_fields([('example', Any), ('inference', Any), |
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We don't generally today, but we could for a very limited set of handlers. The ones I can think of with predictable output types are hugging face pipelines and vLLM; the rest are all dependent on the model.
I think this is probably worth doing when we can, it probably requires some slight modification to the PredictionResult type, though, and might be worth scoping into a follow on PR.
Signed-off-by: Jeffrey Kinard <[email protected]>
Signed-off-by: Jeffrey Kinard <[email protected]>
Signed-off-by: Jeffrey Kinard <[email protected]>
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #33406 +/- ##
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+ Coverage 57.38% 57.42% +0.03%
Complexity 1475 1475
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Files 973 980 +7
Lines 154978 155311 +333
Branches 1076 1076
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+ Hits 88939 89187 +248
- Misses 63829 63908 +79
- Partials 2210 2216 +6
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Signed-off-by: Jeffrey Kinard <[email protected]>
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This PR adds support for calling RunInference with preliminary support for VertexAI through the use of the
VertexAIModelHandlerJSONModelHandler.In order to implement more robust validation for the transform, the
SafeLineLoaderwas refactored out ofyaml_transform.pyinto a separateyaml_utils.pyfile to avoid import cycles.Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:
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